I am looking for an efficient way for editing/reading pixels from Mat (or Mat3b) variable.
I have used :-
Image.at<Vec3b>(i,j)
but it seems to be very slow.
I also used this:-
A.data[A.channels()*A.cols*i + j + 0]
but the problem I am facing with this is when I run this loop
for(i=0; j<A.rows; i++){
for(j=0; j<A.cols; j++){
A.data[A.channels()*A.cols*i + j + 0] = 0;
A.data[A.channels()*A.cols*i + j + 1] = 0;
A.data[A.channels()*A.cols*i + j + 2] = 0;
}
}
only a portion of image is blackened.
Here you can see some of the possibilities for fast element access.
But if you want to do it your way, you need to add a bracket. Otherwise you index computation is not correct:
for(int i=0; i<A.rows; i++){
for(int j=0; j<A.cols; j++){
A.data[A.channels()*(A.cols*i + j) + 0] = 0;
A.data[A.channels()*(A.cols*i + j) + 1] = 0;
A.data[A.channels()*(A.cols*i + j) + 2] = 0;
}
}
But the layout of the memory is not guaranteed to be contiguous due to padding. So according to this you should rather use a formula like this:
for(int i=0; i<A.rows; i++){
for(int j=0; j<A.cols; j++){
A.data[A.step[0]*i + A.step[1]* j + 0] = 0;
A.data[A.step[0]*i + A.step[1]* j + 1] = 0;
A.data[A.step[0]*i + A.step[1]* j + 2] = 0;
}
}
This is one of the most efficient way for editing/reading pixels from cv::Mat. Create pointer to a row (of specific channel if needed)
for(int i=0; i<A.rows;i++){
uchar* rowi = A.ptr/*<uchar>*/(i);
for(int j=0; j<A.cols; j++){
doProcessOnPixel(rowi[j]);
}
}
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